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Social Media Conversations About High Engagement Sports Team Brands
IIM Kozhikode Society & Management Review Pub Date : 2021-07-16 , DOI: 10.1177/22779752211017275
Simon Chadwick 1 , Alex Fenton 2 , Richard Dron 2 , Wasim Ahmed 3
Affiliation  

This study conducts an analysis of social media discussions related to high engagement sports brands. More specifically, our study examined the English Premier League (EPL); it sought to retrieve data systematically over the same day, weekly, for a period of five months. After this process, we had built 20 datasets and NodeXL was utilized to analyse the data. After we had this data, we were able to use qualitative observations to identify key users and conversations that formed around the EPL as well as the connections between the conversations that arose from the brand’s posts and the people involved in them. We also analyzed the quantitative data underpinning our network visualisations to provide further insights. The most obvious initial finding was that when the EPL tweets, it prompts a large volume of conversations directly related to these tweets. However, we also noted that EPL tweets also help instigate further, sometimes unrelated, tweets and conversations. More specifically, we identified that the visualized network of conversations was of a broadcast form, which is characterized by messages being generated by a central account (the EPL) and shared by a number of decentralized users. Based on our analysis, we propose guidance around (S)ocial media presence, (C)rafting the message, Planned (i)ntervention, (S)pontaneous follow-up, and (M)essage mortality to form the SCISM framework. This framework is likely to be of interest to brands that wish to promote, sustain and benefit from their instigation of social media.



中文翻译:

关于高参与度运动队品牌的社交媒体对话

本研究分析了与高参与度运动品牌相关的社交媒体讨论。更具体地说,我们的研究考察了英超联赛(EPL);它力求在同一天、每周、五个月的时间内系统地检索数据。在这个过程之后,我们建立了 20 个数据集,并使用 NodeXL 来分析数据。获得这些数据后,我们能够使用定性观察来识别围绕 EPL 形成的关键用户和对话,以及品牌帖子产生的对话与参与其中的人员之间的联系。我们还分析了支持我们网络可视化的定量数据,以提供进一步的见解。最明显的初步发现是,当 EPL 发推文时,它引发了与这些推文直接相关的大量对话。然而,我们也注意到 EPL 推文也有助于煽动进一步的、有时是不相关的推文和对话。更具体地说,我们发现可视化的对话网络是一种广播形式,其特点是消息由中央帐户(EPL)生成并由许多分散的用户共享。根据我们的分析,我们提出了围绕 (S) 社交媒体存在、(C) 起草信息、计划 (i) 干预、(S) 自发跟进和 (M) 消息死亡率的指导,以形成 SCISM 框架。希望推广、维持社交媒体并从中受益的品牌可能会对这个框架感兴趣。推文和对话。更具体地说,我们发现可视化的对话网络是一种广播形式,其特点是消息由中央帐户(EPL)生成并由许多分散的用户共享。根据我们的分析,我们提出了围绕 (S) 社交媒体存在、(C) 起草信息、计划 (i) 干预、(S) 自发跟进和 (M) 消息死亡率的指导,以形成 SCISM 框架。希望推广、维持社交媒体并从中受益的品牌可能会对这个框架感兴趣。推文和对话。更具体地说,我们发现可视化的对话网络是一种广播形式,其特点是消息由中央帐户(EPL)生成并由许多分散的用户共享。根据我们的分析,我们提出了围绕 (S) 社交媒体存在、(C) 起草信息、计划 (i) 干预、(S) 自发跟进和 (M) 消息死亡率的指导,以形成 SCISM 框架。希望推广、维持并从社交媒体的煽动中受益的品牌可能会对这个框架感兴趣。根据我们的分析,我们提出了围绕 (S) 社交媒体存在、(C) 起草信息、计划 (i) 干预、(S) 自发跟进和 (M) 消息死亡率的指导,以形成 SCISM 框架。希望推广、维持社交媒体并从中受益的品牌可能会对这个框架感兴趣。根据我们的分析,我们提出了围绕 (S) 社交媒体存在、(C) 起草信息、计划 (i) 干预、(S) 自发跟进和 (M) 消息死亡率的指导,以形成 SCISM 框架。希望推广、维持并从社交媒体的煽动中受益的品牌可能会对这个框架感兴趣。

更新日期:2021-07-16
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